Which outcome is expected when performing a Data Privacy Impact Assessment (DPIA) in CPMAI projects?

Which outcome is expected when performing a Data Privacy Impact Assessment (DPIA) in CPMAI projects?

• A. To optimize numeric performance metrics of the model.
• B. To document vendor pricing and procurement requirements.
• C. To evaluate privacy risks and mitigations for AI data processing.
• D. To plan marketing rollout strategies.

Answer: (C)

A Data Privacy Impact Assessment in CPMAI projects focuses on identifying how data is collected, stored, processed, and shared by AI systems and then pinpointing privacy risks tied to that processing. The main outcome is a documented assessment of those risks, including their likelihood and potential impact, plus a clear set of mitigations to reduce them to an acceptable level. This often covers safeguards like data minimization, access controls, anonymization or pseudonymization, retention limits, and governance processes, all linked to a plan for implementing these measures and a record of accountability. In CPMAI contexts, conducting the DPIA helps ensure privacy-by-design and regulatory compliance when working with large-scale or sensitive data, training datasets, and AI outputs. The other themes—improving numerical model metrics, detailing vendor pricing, or planning marketing rollout—do not address evaluating and mitigating privacy risks in AI data processing.

A Data Privacy Impact Assessment in CPMAI projects focuses on identifying how data is collected, stored, processed, and shared by AI systems and then pinpointing privacy risks tied to that processing. The main outcome is a documented assessment of those risks, including their likelihood and potential impact, plus a clear set of mitigations to reduce them to an acceptable level. This often covers safeguards like data minimization, access controls, anonymization or pseudonymization, retention limits, and governance processes, all linked to a plan for implementing these measures and a record of accountability. In CPMAI contexts, conducting the DPIA helps ensure privacy-by-design and regulatory compliance when working with large-scale or sensitive data, training datasets, and AI outputs. The other themes—improving numerical model metrics, detailing vendor pricing, or planning marketing rollout—do not address evaluating and mitigating privacy risks in AI data processing.